Unit 3 On the move
ReadingSelf-driving cars一destination known?
自动驾驶汽车•一目的地吗？
Mr Zhang casually glances at the empty driver's seat and says, “Destination Grand Hotel. Family mode. Start." The car responds immediately, easing smoothly into the busy traffic and avoiding obstacles on the road. Inside the car, the family have chosen their entertainment from a pop-up display panel, ready for the journey ahead. This imagined scene provides a likely future reality for self-driving cars, also known as autonomous vehicles(AVs).
张先生漫不经心地看了-眼空荡荡的驾驶座，说道:“目的地格兰酒店。家庭 模式。出发。”汽车立即响应，平稳驶入繁忙的车流，避开路上的障碍。车里面， 一家人已经在弹出式显示面板上选好了娱乐工程，为前方的旅途作好准备。这个 想象中的场景展示了自动驾驶汽车，也叫自主汽车，一种可能的未来的现实。
However, before this evolution in transport becomes a revolution, it must be fully understood how self-driving cars work. Put simply, self-driving cars must "see" and "behave" appropriately to be safe on the road. They do this through various hardware and deep-learning AL Cameras as well as sensors like radar and lidar capture a variety of data from the external environment. Once the data is sent to the AI system, the "brain" of the car, it is analysed and put together like a puzzle so that the self-driving car can Hseen its surroundings and determine its position. Meanwhile, the Al system identifies patterns from the data and learns from them. An action plan is then created to instruct the car how to "behave" in real time: stay in the lane, move into another one, speed up or slow down. Next, the necessary mechanical controls, such as the accelerator and brakes, are activated by the AI system, allowing the car to move in line with the action plan.
然而，在这种交通方式的变革成为一场革命之前，必须充分了解自动驾驶汽 车的工作原理。简言之，要想在路上平安行驶，自动驾驶汽车必须恰当地“看” 和“做L它们通过各种硬件和深度学习人工智能(AI)来实现。摄像头以及雷达、 激光雷达等传感器从外部环境中获取各种数据。数据一日发送到人工智能系统， 即自动驾驶汽车的“大脑”，立即被分析并像
拼图一样被拼凑起来，于是汽车就能 “看到”周围的环境并确定自身方位。同时，人工智能系统从数据中识别出模式， 从中学习。然后一份行动计划被创立出来，用以指导汽车如何实时"行动''：沿车 道行进，变道，加速或减速。接下来，人工智能系统激活油门、刹车等必要的机 械操纵装置，让汽车按照行动计划行驶。
This may sound perfect in theory, but in reality technological barriers in AV development exist. The self-driving car*s perception system presents one. Road traffic in the real world is so complicated that unfamiliar or unexpected conditions may occur at any time. Since it is unreasonable for the database to include every possible object in every possible condition ahead of time, the system might not recognize everything on the road. In one tragic real-life case,a self-driving car's perception system failed to identify a white truck against the bright, sunlit sky. It assumed that there was no obstacle in its path and did not activate the brakes, causing the death of the driver in the self-driving car. Accidents like this pose the question of how self-driving cars can better learn and improve their behaviours on the road to ensure safe journeys.
这理论上听起来很完美，但实际上，自动驾驶汽车的开发还存在技术障碍。 其感知系统就是一个例子。真实世界中的道路交通如此复杂，以至于不熟悉或意 外的情况时有发生。既然数据库将每种可能发生的情况下的每个可能存在的物体 都预先包含是不合理的，系统就无法识别路上所有东西。在一个悲惨的真实案例 中，一辆自动驾驶汽车的感知系统未能从明亮晴空的背景下识别一辆白卡车。 它只当行进路线上没有障碍物，没刹车，导致自动驾驶汽车的司机死亡。此类事 故提出了这样一个问题，即自动驾驶汽车怎样才能更好地学习，改进行驶中的行 为以确保平安出行。
Another aspect that needs careful consideration is the ethical responses self-driving cars would make in specific circumstances. The Trolley Problem is often used to discuss difficult ethical choices they may face. For example, should those in the self-driving car always be protected first even if it means endangering the lives of pedestrians? Should a self-driving car hit a single pedestrian to avoid crashing into a group of pedestrians? And would it make a different decision if the pedestrian were a child or a senior citizen? The moral dilemma that comes with how to ethically program self-driving cars has yet to be resolved.
另一个需要仔细斟酌的方面是自动驾驶汽车在特定情况下的伦理反响。人 们经常援引“电车难题”来讨论自动驾驶汽车可能面临的棘手的伦理抉择。例如， 自动驾驶汽车内的人是否应该始终受到优先保护，即使这意味着危及行人的生命? 为防止撞到一行人，自动驾驶汽车是否应该去撞一个行人？这个行人如果是一 个小孩或老人，自动驾驶汽车会作出不同的决定吗?如何编写程序让自动驾驶汽 车合乎伦理，这个问题带来的伦理困境尚待解决。
Besides such ethical concerns, the legal situations the AV industry is likely to be confronted with have fuelled heated debates. In this emerging industry, manufacturing and programming standards are not yet uniform. Moreover, the quality and safety of AV technology is still being challenged. This could lead to extraordinary cases like who should be held responsible when self-driving cars are involved in accidents-should it be the driver, the software programmer or the manufacturer? Manufacturing and programming standards first have to be agreed upon to make it possible for law courts to decide who is at fault when things go wrong. As advances in AV design and technology are in progress, the final agreement on laws and regulations in this industry remains to be seen.
除了这些道德方面的担忧，自动驾驶汽车行业可能面临的法律处境已经 引发了激烈争论。在这个方兴未艾的行业里，制造和编程标准尚未统一。此外， 自动驾驶汽车技术的可靠性和平安性依然受到质疑。这会导致一些意想不到的情 况，例如，当自动驾驶汽车发生事故时，责任该由哪一方承当一是自动驾驶汽 车的司机，软件程序员，还是生产商?首先要有统一的制造和编程标准，法庭才 能在出现问题时裁定谁有过错。自动驾驶汽车的设计和技术正在不断进步，而管 理该行业的法律法规的最终-致尚待确定。
There can be little doubt that, despite all the challenges, self-driving cars will form part of our future. The question is, what is next? Some argue that self-driving cars should be allowed to operate without human control, while others are more cautious and believe that human operation, even if limited, is necessary in successful AV design. Only time will reveal its true path. While the journey ahead is not without obstacles, the eventual destination is bound to be another milestone for humankind's amazing vision and inventiveness.
毫无疑问，尽管困难重重，但自动驾驶汽车将成为我们未来重要的一局部。 问题是接下来
会怎样?有些人主张应该让自动驾驶汽车在无人控制的情况下运 行，而另一些人那么更谨慎些，认为人工操控，即使是有限的，仍然是有必要的。 只有时间才能揭示出正确的道路。虽然前方绝非坦途，但最终目的地必将成为人 类惊人远见和创造力的又一座里程碑。
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